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Traffic-sign recognition plays an important role in road transportation systems. This letter presents a novel two-stage method for detecting and recognizing traffic signs from mobile Light Detection and Ranging (LiDAR) point clouds and digital images. First, traffic signs are detected from mobile LiDAR point cloud data according to their geometrical and spectral properties, which have been fully studied in our previous work. Afterward, the traffic-sign patches are obtained by projecting the detected points onto the registered digital images. To improve the performance of traffic-sign recognition, we apply a convolutional capsule network to the traffic-sign patches to classify them into different types. We have evaluated the proposed framework on data sets acquired by a RIEGL VMX-450 system. Quantitative evaluations show that a recognition rate of 0.957 is achieved. Comparative studies with the convolutional neural network (CNN) and our previous supervised Gaussian–Bernoulli deep Boltzmann machine (GB-DBM) classifier also confirm that the proposed method performs effectively and robustly in recognizing traffic signs of various types and conditions. [ABSTRACT FROM AUTHOR]

Because of the hierarchical significance of traffic sign images, the traditional methods do not effectively control and extract the brightness and features of layered images. Therefore, an automatic recognition algorithm for traffic signs based on a convolution neural network is proposed in this paper. First, the histogram equalization method is used to pre-process the traffic sign images, with details of the images being enhanced and contrast of the images improved. Then, the traffic sign images are recognized by a convolution neural network and the large scale structure of information in the traffic sign images are obtained by using a hierarchical significance detection method based on graphical models. Next, the area of interest in the traffic sign images are extracted by using the hierarchical significance model. Finally, the Softmax classifier is selected to classify the input feature images to realize the automatic recognition of traffic signs. Experimental results show that the proposed algorithm can control the brightness of traffic sign images, which can accurately extract image regions of interest and complete the automatic recognition of traffic signs. [ABSTRACT FROM AUTHOR]

Growth in the transportation sector in urban areas was very high. This resulted in an increase in the number of vehicles and congestion on the highway. Public Transportation was a vehicle that causes a lot of traffic jam and made the road feel more crowded. In addition, public transportation also often violated rules such as entering into a residential housing lane to avoid overcrowding of vehicles on the highway. The violation of public transportation was by entering and passing through the residential area which was an area that must be free from the flow of public transportation. In addition, there were also traffic signs to prohibit public transportation from passing. To overcome this problem, this study proposed a system to identify and distinguish types of public transportation from other types of vehicles based on colour images. The system processes were carried out through several stages, including offline video capture, video frame processes, background and foreground separation (background subtraction), morphology (opening), bitwise and, images rectangular crop, HSV colour space conversion and HSV histogram creation. The results of the HSV colour space conversion in the histogram were used for the identification process in determining whether the city transportation existed or not by using Learning Vector Quantization method. The results of the system testing using Learning Vector Quantization method with 30Fps frame rate video test data were capable to recognize 66 images of public transportation and not public transportation from 78 videos of car typed of vehicle, obtained success with a percentage of 84.62%. And 60Fps frame rate video test data was able to recognize 71 images of public transportation and not public transportation from 78 videos of car typed of vehicle, obtained success with a percentage of 91.03%. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Guangxi Normal University - Natural Science Edition is the property of Gai Kan Bian Wei Hui and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

A widespread opinion holds that norms and codes of conduct as such can only be established via words, that is, in some lexical form. This perspective can be criticized: some norms produced by human acts are not word-based at all. For example, many norms are actually conveyed through graphics (e. g. road signs and land-use maps), sounds (e. g. the referee's whistle), a silent gesture (the traffic warden's signal to halt). In this article, we will focus on the norms that are created by means of drawings and can be termed "drawn norms" or "graphical norms." Specifically, we will inquire into the phenomenon of graphical norms with particular regard to traffic signs and land-use plans, and we will discuss the philosophical and legal problems to which these phenomena give rise. [ABSTRACT FROM AUTHOR]

Copyright of Chinese Journal of Liquid Crystal & Displays is the property of Chinese Journal of Liquid Crystal & Displays and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The San Pablo/I-80 corridor is a “SMART” transportation corridor that extends about 20 miles along the eastern shore of the San Francisco Bay. The corridor uses Intelligent Transportation System (ITS) technologies to increase and enhance transportation mobility.The goal of the SMART Corridor Plan was to improve vehicle mobility throughout the corridor. Since the plan focused almost exclusively on vehicular traffic, achieving these goals has the potential to raise the risk of injury to pedestrians and bicyclists without thorough analysis of the overall effects of the SMART corridor implementation.This study identifies and describes multiple factors that may affect the behavior of pedestrians, bicyclists and drivers along the corridor. This report focuses on findings for the Berkeley sector.The evaluation utilized multiple types of data collection including vehicle counts, field observations, field inspections, and collision data. Researchers inspected the physical elements of each intersection and observed driver, pedestrian, and bicyclist behavior. Analysis of these data led to a typology, used to assign context-specific safety interventions, many of which involve engineering and enforcement.The main goal is to ensure that motorists as well as pedestrians and bicyclists should have a sense that all have an equal right to travel in the area. This can be accomplished through clear and consistent signage, a distinctive crosswalk treatment, consistent lighting and other enhancements.Implementation of the recommended countermeasures and follow up analysis are not part of this baseline study. A detailed traffic engineering analysis would be required to produce estimates of costs and benefits, and to determine priorities.

Road traffic signs are part of the road infrastructure components meant to ensure the safe use of roads by motorists and pedestrians alike. A good knowledge and comprehension of road signs helps ensure smooth flow of traffic, improves safety for other motorists and provides drivers with good reaction time to comply with the message dictated by the signs. Abu Dhabi, being the capital of the UAE, brings together people from all over the world for work, business or tourism. Abu Dhabi has quality roads and traffic signage together with an efficient police force that enforces adherence to traffic rules. Despite all these and the reduced fatalities in absolute terms, traffic violations have been increasing exponentially, resulting in five million traffic fines in 2019 for a population of about 2.9 million inhabitants. This study sought to assess motorists’ comprehension of the various traffic signs used across the UAE. The results of the survey (N = 200) revealed that the drivers were able to correctly identify 77% of the road signs in the survey. It was also found that the respondents failed to correctly identify traffic signs within the specific category referred to as “advance warning signs”. Respondents’ education, nationality, gender, and marital status did not have any statistically significant effects on the results compared to earlier studies. It is recommended that more attention be focused on driver education and training.

Advanced Driver Assistance System (ADAS) represents a collection of vehicle-based intelligent safety systems. One in particular, Traffic Sign Recognition System (TSRS), is designed to detect and interpret roadside information in the form of signage. Even though TSRS has been on the market for more than a decade now, the available ones differ in hardware and software solutions they use, as well as in quantity and typology of signs they recognize. The aim of this study is to determine whether differences between detection and readability accuracy of market-ready TSRS exist and to what extent, as well as how different levels of “graphical changes” on the signs affect their accuracy. For this purpose, signs (“speed limit” and “prohibition of overtaking”) were placed on a test field and 17 vehicles from 14 different car brands underwent testing. Overall, the results showed that sign detection and readability by TSRS differ between car brands and that even small changes in the design of signs can drastically affect TSRS accuracy. Even in a controlled environment where no sign has been altered, there has been a 5% margin of misread signs.

In advanced driver assistance systems, accurate detection of traffic signs plays an important role in extracting information about the road ahead. However, traffic signs are persistently occluded by vehicles, trees, and other structures on road. Performance of a detector decreases drastically when occlusions are encountered especially when it is trained using full object templates. Therefore, we propose a new method called discriminative patches (d‐patches), which is a traffic sign detection (TSD) framework with occlusion handling capability. D‐patches are those regions of an object that possess the most discriminative features than their surroundings. They are mined during training and are used for classification instead of the full object templates. Furthermore, we observe that the distribution of redundant‐detections around a true‐positive is different from that around a false‐positive. Based on this observation, we propose a novel hypothesis generation scheme that uses a voting and penalisation mechanism to accurately select a true‐positive candidate. We also introduce a new Korean TSD (KTSD) dataset with several evaluation settings to facilitate detector's evaluation under different conditions. The proposed method achieves 100% detection accuracy on German TSD benchmark and achieves 4.0% better detection accuracy, when compared with other well‐known methods (under partially occluded settings), on KTSD dataset.

Traffic signs are the basic elements of communication between the relevant road authorities and road users. They manage, regulate, inform and warn road users to ensure their safe movement throughout transport networks. Traffic signs must be timely visible to all traffic participants in all weather and traffic conditions in order to fulfil their function, which means they must have satisfactory retroreflection properties. This paper presents a research of the deterioration of traffic signs retroreflection. The aim of this article is to develop models that will effectively enable predicting the retroreflection of traffic signs and thus optimize the maintenance activities and replacement of road signs to increase road safety. The research included measurements of retroreflection of retroreflective material Classes I and II (white, red and blue colour) and Class III (red and yellow colour). Based on the collected data from the City of Zagreb (Republic of Croatia), the authors developed the models to estimate the functional service life of certain colours and materials used to make traffic signs. Considering that the average coefficient of determination for all the models is between 0.55-0.60, they present an effective tool in the traffic sign maintenance system.

Background and aims: Usability is the extent to which a system, product or service can be used by specified users to achieve specified goals with effectiveness, efficiency and satisfaction in a specified context of use. Increased public awareness of the usability issues has caused that usability plays an important role in production. Brooke’s SUS is one of the most used tool for measuring usability. Yet, the Persian translation of this tool has not been available to Iranian researchers, and therefore this study has been conducted in order to provide the Persian translation of it and measure its psychometric validation in assessing usability of traffic signs. Methods: Modified version of SUS by Annie(2011) was translated using Backward-Forward method of translation. For measuring validity of the questionnaire the opinions of 10 experts in related field were used. Content Validity Ratio (CVR) was measured based on Lawshi method and Content Validity Index (CVI) was measured based on Waltz and Basel method. The questionnaire content validity index was also calculated.There is 10 items in SUS for assessing usability of each traffic sign, therefore for assessing usability of 20 selected traffic signs, a 200 items questionnaire was developed. Questionnaires were distributed among 50 staff of Iran University of Medical Sciences. Cronbach’s α was used was used to measure the reliability of the questionnaire. Stability of questionnaire was calculated by using test – retest and intra-cluster correlation index. Results: All the items in SUS showed a high level of CVR and all items were accepted. CVI of all items were above the acceptable level of 0.79 . Content validity index was equal to 0.927. Cronbach’s α was equal to 0.965, and inter-cluster correlation index was equal to 0.993. Conclusions: The Persian version of SUS is a reliable tool for measuring usability level and showed a high level of validity and reliability and can be used for future researches in the field of usability.

Background: About 1.25 million people die each year as a result of road traffic crashes.90% road traffic deaths occurs in low and middle income countries. Urgent action is needed to achieve the target halving the global number of deaths and injuries from road traffic crashes by 2020. Objective: The study conducted to assess the knowledge of traffic signs among the post graduate student; and to find out association of various socio-demographic and other variable with knowledge of traffic signs. Methods –A cross sectional study was conducted in 2017 on 100 post graduate students. Data was collected using predesigned, semi structured proforma .Data analysis was done by using SPSS version20. Results –Overall mean score for knowledge of traffic signs was found to be 52, while mean score in mandatory sings, cautionary sign & informatory sign were around 62, 44 & 54 respectively. Knowledge was significantly higher in males and in owner of both two wheeler & four wheeler (p

The most of legal theories in the twentieth century have always asserted that rules are product of linguistic utterances and that they have nothing to do with "visual culture". In this paper I show, on the contrary, that the visual dimension is crucial to understand and found some legal-philosophical discourse. The relationship between images and law is always bi-directional, by the first direction following the way from law to images, and by the second one, vice versa, passing from images into the universe of normative discourse. In these pages I do not explore the second direction; I limit myself to investigate the first way asking two questions relevant for the construction of the legal order: Are there visual signs in the normative language? And, if so, what function do they have? [ABSTRACT FROM AUTHOR]

Traffic signs are used to control and regulate traffic and create a safe environment for road users. Therefore, it is of great importance to ensure that road signs are easily understood and easily learned, especially by drivers. The current study, conducted in Israel, focused on the ability to learn unfamiliar road signs and on the effect of the compliance of those signs with principles of physical and conceptual compatibility (ergonomic principles for symbol design). A preliminary experiment tested the extent to which each of 30 signs, not used in Israel, complied with the compatibility principle. Based on this evaluation, the signs were divided into two distinctive groups - "ergonomic" signs and "non-ergonomic" signs. In the second part of the study, we tested the differences between the two groups of signs in terms of comprehension and learnability, conducting recognition-recall tests among 33 teenagers without a driving license. Results showed a significant design main effect, with a higher comprehension level associated with the ergonomic signs compared to the non-ergonomic signs. A significant learnability main effect was also found, with comprehension levels in the recall test significantly higher than in the recognition test for both groups of signs. In addition, the probability for improvement in comprehension based on learning the meanings of the signs was higher among the ergonomic group of signs. These findings demonstrate the importance of ergonomic design in shaping the understandability and learnability of road signs. The implications of the current results can be most relevant to tourists, as well as novice drivers. [ABSTRACT FROM AUTHOR]

• An original methodology has been generated for classifying traffic signs. • The well-consolidated tracking task is used for evaluating their effect on movement. • Non-representative traffic signs provoke counterproductive effects. The effect of traffic signs in the motor behavior of drivers is not fully understood yet. Knowing about how humans process the meaning of signs will improve response time to those signs and the decision making carried out when driving. Literature shows that the signs that are not-well designed produce counterproductive effect on movement. This study sounds out which are precisely the warning, Ecuadorian-traffic signs more ergonomic for participants, from a cognitive point of view, and classifies them by using the criteria of representativity, univocity and numbers of errors provoked by them. With this, it can be detected which traffic signs need to be redesigned. The economic, social and psychological consequences of car accidents are well-known. Every single effort orientated to the solution of this social problem is welcome. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Qadisiyah Computer Science & Mathematics is the property of Republic of Iraq Ministry of Higher Education & Scientific Research (MOHESR) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

When driving a vehicle, do we read the words displayed on traffic signs just as we do in more standard conditions? In the driving context, stimulus quality is generally worse, and reading has to be performed at the same time as we are doing other tasks. In the present work, we examined the effects of word frequency and word length on reading in such circumstances. A stimulus presentation mimicking the approach to the traffic sign increased the effect of word frequency, but not the effect of word length, on reading latency. In addition, performing the reading task while driving along a simulated route produced similar results. Therefore, in the context of the driving activity, the advantage of high-frequency over low-frequency words seems to be even more relevant than in standard conditions. Traffic sign designers can consider these results when deciding the most appropriate word in a variable message sign. [ABSTRACT FROM AUTHOR]

Traffic sign detection is a crucial step for automatic driving and Intelligent Transportation. Promising results have been achieved in the area of traffic sign detection, but most of them are limited to ideal environment, where the traffic signs are very clear and large. Actually, traffic sign detection is always realized based on object detection methods. However, existing object detection methods failed to detect most of the traffic signs, especially in surveillance videos or driving recorder videos. In fact, traffic signs, i.e. traffic lights, or distant road signs in driving recorded video, always cover less than 5% of the whole image in the view of camera. Therefore, in this paper, we dedicate an effort to propose a real-time small traffic sign detection approach based on revised Faster-RCNN. More specifically, firstly, we use a small region proposal generator to extract the characteristics of small traffic signs. That is to say, considering that the stride of generator is too large, we remove the pool4 layer of VGG-16 and adopt dilation for ResNet. Secondly, we combine the revised architecture of Faster-RCNN with Online Hard Examples Mining (OHEM) to make the system more robust to locate the region of small traffic signs. Finally, we conduct extensive experiments and empirical evaluations on several different videos to demonstrate the satisfying performance of our approach. i.e., the experimental results show our approach improve the mean average precision by 12.1% over the original object detection algorithm. [ABSTRACT FROM AUTHOR]

This study assesses the impact of traffic sign deficit on road traffic accidents in Nigeria. The participants were 720 commercial vehicle drivers. While simple random sampling was used to select 6 out of 137 federal highways, stratified random sampling was used to select six categories of commercial vehicle drivers. The study used qual-dominant mixed methods approach comprising key informant interviews; group interviews; field observation; policy appraisal and secondary literature on traffic signs. Result shows that the failure of government to provide and maintain traffic signs in order to guide road users through the numerous accident black spots on the highways is the major cause of road accidents in Nigeria. The study argues that provision and maintenance of traffic signs present opportunity to promoting safety on the highways and achieving the sustainable development goals. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Traffic & Transportation Research / Trafik ve Ulaşım Araştırmaları Dergisi is the property of Journal of Traffic & Transportation Research and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

A group of adult individuals with dyslexia and a matched group of normally reading individuals participated in a driving simulation experiment. Participants were asked to read the word presented on every direction traffic sign encountered along a route, as far as possible from the sign, maintaining driving performance. Word frequency and word length were manipulated as within-subject factors. We analyzed (a) reading accuracy, (b) how far the sign was when the participant started to give the response, (c) where the participant looked during the time leading up to the response, and (d) the variability of the vehicle's speed during that time and during driving on similar segments of the route that did not present the traffic signs. Individuals with dyslexia showed lower levels of performance in the reading task, the roles of word frequency and word length were more influential for them, and there was larger variability of the vehicle's speed during the time they were attempting to read the traffic sign, which did not occur during their driving on similar segments that did not present the targeted traffic signs. Therefore, the specific needs of individuals with dyslexia on the road should be considered in plans aimed at increasing traffic safety and fluidity. [ABSTRACT FROM AUTHOR]

Traffic signs plays an important role in pedestrian path guidance in the urban rail transit hub. However, the existing traffic signs within urban rail transit hubs are more or less deployed rigidly, which cannot fully consider the relationship between the layout and visual information about passengers' decisions. Therefore, this paper analyses the influence of traffic signs on the path selection behavior of pedestrians, and construct the MAKLINK diagram to study the impact of traffic signs on pedestrians' proceeding decisions by a simulation technique. With the MAKLINK diagram, the path plan under the guidance of traffic signs is formulated. Then, the optimal pedestrian path on the MAKLINK diagram considering the effect of traffic signs is optimized via the Ant Colony Algorithm. An empirical study at Beijing South Railway Station is conducted. The findings reflect that traffic signs within urban rail transit hub could effectively take effect to the path selection behavior of large-volume passengers. [ABSTRACT FROM AUTHOR]

In this study, the authors present a new efficient method based on discriminative patches (d‐patches) for holistic traffic sign detection with occlusion handling. Traffic sign detection is an important part in autonomous driving, but usually hampered by the occlusions encountered on roads. They propose a method which basically upgrades d‐patches by integrating vocabulary learning features. Consequently, d‐patches are more discriminatively trained for robust occlusion handling. In addition, a holistic classifier is trained on d‐patches, which identify those regions where occlusion exists. This results in higher confidence‐score for the regions which contain traffic signs and lower confidence‐score for the regions containing occlusions. Furthermore, they also propose a new coarser‐to‐fine (CTF) approach to speed up the traffic sign detection process. CTF minimises the use of traditional sliding window for object detection. It relies on colour variance to search the regions with high probability of traffic sign presence. Sliding window is used only on the selected high probability regions. The proposed method achieves 100% detection results on German Traffic Sign Detection Benchmark and performs 2.2% better than the previous state‐of‐the‐art methods on Korean Traffic Sign Detection dataset, under partially occluded settings. By using CTF approach, five times speedup with a marginal loss in accuracy can be achieved. [ABSTRACT FROM AUTHOR]

Persons or objects on signs seem to have a culturally preferred direction of facing (Kumakura, 1990). Is such a difference in direction also true of pictures on traffic signs between Japan and Germany? People in Japan and Germany drive on the left and the right side of the road, respectively. In this respect, a question arises: Does the difference between left-hand and right-hand traffic in these two countries influence the way the pictures on traffic signs face? The aim of this study is threefold: 1) to collect functionally equivalent traffic signs in Japan and Germany; 2) to compare the pictures on the signs between these countries with respect to their facing directions; and 3) to try to clarify whether and to what extent differences in facing directions are found on the traffic signs. The results are expected to contribute to the study of the relationship between writing directions and facing directions of pictures. [ABSTRACT FROM AUTHOR]

There are many intersection roads in the urban road, and the intersection is often a necessary place for the vehicle to complete the swerve and for the agminated foot passengers to across the street. Most of the roads in mountainous cities have deformed intersections. Therefore, the location selection of traffic signs at a mountain road intersection is particularly important. Based on the driving characteristics, this paper discusses the location selection of related traffic signs at the intersection. According to the brief analyses on intersection characteristics in mountainous city and based on drivers' specific visual reaction, the related visual dynamic states for drivers are determined. On the strength of drivers' visual reference frame, the specific location of traffic sign at road intersection in mountainous city is installed. [ABSTRACT FROM AUTHOR]

This article discusses a rare instance of the highest national courts explicitly addressing traffic signs in their judgments or decisions. It critically examines the standpoint expressed by the Polish Constitutional Tribunal and the Supreme Court, according to which the basic traffic sign categories in Poland—obligatory, prohibitory, informative and warning—are not separable (not disjunctive) [e.g. prima facie non-normative signs (informative or warning) can also be normative (obligatory or prohibitory)]. These courts formulated this idea when addressing the legal question concerning the applicability of legal provision penalizing failure to comply with a traffic sign to parking a car without paying a fee in an area marked by an informative sign that indicates the need to charge a fee for parking. The article analyses and criticizes the relevant standpoint of the Polish Constitutional Tribunal and the Supreme Court. It shows how many negative consequences can result from frivolous treatment and neglect of traffic signs. It also reconstructs some possible practical recommendations concerning not only traffic signs but also visualizations of legal rules in general. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Chongqing University of Posts & Telecommunications (Natural Science Edition) is the property of Chongqing University of Posts & Telecommunications and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Two recycled high-density polyethylene specimens and two recycled high-density polyethylene blends were characterized in terms of their thermal and mechanical properties with the purpose of assessing their suitability for the construction of traffic signs. Traffic signs constructed from recycled plastics provide an application for materials that otherwise with end up in landfills. The HDPE composite containing 25% LDPE and 5% ABS had the best mechanical and thermal performance. Of importance is the recycling of ABS that traditionally had not been recycled locally and found its final fate in landfills.

There has been an increasing concern about inactive drivers who would easily lead to road accidents and fatalities once return to driving. This study investigated the re-usability of traffic signs for inactive drivers with consideration of driver factors and cognitive sign features. Fifty-seven Hong Kong Chinese, who possessed a full driving license but had not driven for an extended period, comprehended the meanings and rated the cognitive features of 21 traffic signs. The re-usability performance of participants who had not driven for at least a year was similar to those who had not been driving since obtaining driving license. The re-usability of traffic signs was better when the signs were familiar, concrete, simple and meaningful. To improve sign re-usability, designers should consider the cognitive sign features, provide direct and unambiguous visualization for underlying concepts, make better use of eye-catching design elements, and proper juxtaposition of similar pictorials in sign design.

Mapping with surveying equipment is a time-consuming and cost-intensive procedure that makes the frequent map updating unaffordable. In the last few years, much research has focused on eliminating such problems by counting on crowdsourced data, such as GPS traces. An important source of information in maps, especially under the consideration of forthcoming self-driving vehicles, is the traffic regulators. This information is largely lacking in maps like OpenstreetMap (OSM) and this article is motivated by this fact. The topic of this systematic literature review (SLR) is the detection and recognition of traffic regulators such as traffic lights (signals), stop-, yield-, priority-signs, right of way priority rules and turning restrictions at intersections, by leveraging non imagery crowdsourced data. More particularly, the aim of this study is (1) to identify the range of detected and recognised regulatory types by crowdsensing means, (2) to indicate the different classification techniques that can be used for these two tasks, (3) to assess the performance of different methods, as well as (4) to identify important aspects of the applicability of these methods. The two largest databases of peer-reviewed literature were used to locate relevant research studies and after different screening steps eleven articles were selected for review. Two major findings were concluded—(a) most regulator types can be identified with over 80% accuracy, even using heuristic-driven approaches and (b) under the current progress on the field, no study can be reproduced for comparative purposes nor can solely rely on open data sources due to lack of publicly available datasets and ground truth maps. Future research directions are highlighted as possible extensions of the reviewed studies.

We can see arising trend in the automotive industry in last years – autonomous cars that are driven just by on-board computers. The traffic signs tracking system must deal with real conditions with data that are frequently obtained in poor light conditions, fog, heavy rain or are otherwise disturbed. Completely same problem is solved by mapping companies that are producing geospatial data for different information systems, navigations, etc. They are frequently using cars equipped with a wide range of measuring instruments including panoramic cameras. These measurements are frequently done during early morning hours when the traffic conditions are acceptable. However, in this time, the sun position is usually not optimal for the photography. Most of the traffic signs and other street objects are heavily underexposed. Hence, it is difficult to find an automatic approach that can identify them reliably. In this article, we focus on methods designed to deal with the described conditions. An overview of the state-of-the-art methods is outlined. Further, where it is possible, we outline an implementation of the described methods using well-known Open Computer Vision library. Finally, emphasis is placed on the methods that can deal with low light conditions, fog or other situations that complicate the detection process.